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J Biomed Semantics. 2016 May 10;7:25. doi: 10.1186/s13326-016-0064-2. eCollection 2016.

OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

Author information

School of Computing, University of South Alabama, Mobile, Alabama, 36688-0002 USA.
Computer and Information Science Department, University of Oregon, Eugene, Oregon, 97403-1202 USA.
Miracle Query, Inc., Eugene, Oregon, 97403-1202 USA.
Department of Philosophy, University at Buffalo, Buffalo, New York, 14260-4150 USA.
Genome Informatics, The Jackson Laboratory, Bar Harbor, Maine, 04609-1523 USA.
Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, 84112-5775 USA.
Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington D.C., 20007-1485 USA.
Center for Computational Science, University of Miami, Miami, Florida, 33146-2960 U.S.A.
Department of Microbiology and Immunology, First Affiliated Hospital, Kunming Medical University, Kunming, Yunnan, 650032 China.
Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, 63110-0001 USA.
Mitchell Cancer Institute, University of South Alabama, Mobile, Alabama, 36604-1405 USA.
Department of Biology, University of South Alabama, Mobile, Alabama, 36688-0002 USA.
School of Dental Medicine, University at Buffalo, Buffalo, New York, 14214-8006 USA.


As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: The OmniSearch system is also free and open to all users, accessible at:


Biomedical ontology; Data annotation; Data integration; Non-coding RNA; Ontology development; SPARQL query; Semantic search; Target gene; microRNA

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